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CD critic

Review a finished Data2Story blog against the 5 quality rubric dimensions (visual_design, narrative_pacing, data_method_transparency, claim_data_alignment, insight_value), score each 1-7 with on-page evidence, and emit critic.json with pass/fail + targeted, surgical send-back instructions. Verifies every load-bearing claim/asset against its traceability chain before scoring; applies the caveat-survival, honest-accuracy, and third-party-attribution caps. Does NOT rewrite content — scores and sends back. Use at Stage 6.5 after the Auditor and after verify.py has produced verifier.json; re-runs each revision round. Triggers: a built index.html plus verifier.json exist, or you need to judge whether the article is actually good.

QinghongLin/data2story-skill Claude Code author: QinghongLin 2 files body ≈ 4 452 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Review a finished Data2Story blog against the 5 quality rubric dimensions (visualdesign, narrativepacing, datamethodtransparency, claimdataalignment…

As a process D 48/100 · Unfinished process — References files that are not bundled: ../../frontend-design-pro/references/abstract_excellence.json, ../../dataviz-craft/references/chart_chooser.json, ../../dataviz-craft/references/annotation_layers.json

AnalyzerWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
D
48/100
Unfinished process
References files that are not bundled: ../../frontend-design-pro/references/abstract_excellence.json, ../../dataviz-craft/references/chart_chooser.json, ../../dataviz-craft/references/annotation_layers.json
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(*)
    allowed-tools: Bash(*) Read Write Grep

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../../frontend-design-pro/references/abstract_excellence.json
  • warning missing-ref reference to a missing file: ../../dataviz-craft/references/chart_chooser.json
  • warning missing-ref reference to a missing file: ../../dataviz-craft/references/annotation_layers.json
  • warning missing-ref reference to a missing file: ../../frontend-design-pro/references/pitfalls.json

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: ../../frontend-design-pro/references/abstract_excellence.json, ../../dataviz-craft/references/chart_chooser.json, ../../dataviz-craft/references/annotation_layers.json
  • 0Tools and files. 4 referenced file(s) missing: ../../frontend-design-pro/references/abstract_excellence.json, ../../dataviz-craft/references/chart_chooser.json, ../../dataviz-craft/references/annotation_layers.json
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 4452 tokens
  • 100Steps. 31 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 733: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 31 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.